However, currently available data do not support a causal relationship.We sought to examine whether depressive symptoms and level of Alzheimer's disease (AD) pathology are independently or interactively associated with the risk of progression to mild cognitive impairment (MCI).
The study included a total of 216 participants from the Biomarkers for Older Controls at Risk for Alzheimer's Disease study, a cohort of individuals who were cognitively normal at baseline (mean age=57) and followed for more than 20 years (mean=12.7 years), who had baseline Hamilton Depression Scale (HAM-D) scores and cerebrospinal fluid (CSF) amyloid beta (Aβ), t-tau, and p-tau measures available.
Cox regression demonstrated that baseline HAM-D and CSF AD biomarkers were both associated with time to onset of MCI. There was an interaction between HAM-D scores and markers of AD pathology, in which depression was associated with time of onset in participants with low levels of AD pathology (hazard ratio=0.64; 95% confidence interval=0.43-0.95; =.026).
The effect of depressive symptoms on progression to clinical symptoms of MCI may be most evident among individuals with low levels of AD pathology.
The effect of depressive symptoms on progression to clinical symptoms of MCI may be most evident among individuals with low levels of AD pathology.Plasma markers have been reported to be associated with brain amyloid burden, tau pathology, or neurodegeneration. We aimed to evaluate whether plasma biomarker profiles could predict Alzheimer's disease (AD) pathology and clinical progression in older adults without dementia.
Cross-sectional and longitudinal data of participants enrolled in this study were from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Plasma amyloid beta (Aβ)/Aβratio was selected as the marker for amyloid pathology, p-tau181 for tau pathology, and neurofilament light for neurodegeneration. Cut-offs for these plasma markers were calculated with well-established positron emission tomography and structural imaging biomarkers as reference. Older adults without dementia were categorized into eight groups at baseline by plasma amyloid/tau/neurodegeneration (A/T/N) cut-offs. Clinical progression was analyzed using linear mixed-effects models and Cox proportional hazard models.
A total of 183 participants (97 cognitively normal [CN] subjects and 86 patients with mild cognitive impairment [MCI]; mean age 72.6 years, and 48.1% men) were included. Participants with A+ had significantly higher proportions of apolipoprotein E () gene ?4 carriers than those with A-. Brain atrophy was observed in all groups of CN, whereas cognition decline was obvious in the A+T+N+ group. Compared to A-T-N-, MCI patients with A+T+N+ had faster cognition worsening and faster brain atrophy. In the whole cohort, A+T+N+ and A+T+N- participants were at higher risk of clinical progression.
Plasma A/T/N biomarker profiles may predict AD pathology and clinical progression, indicating a potential role for plasma biomarkers in clinical trials. More research is warranted to develop a robust plasma AD framework.
Plasma A/T/N biomarker profiles may predict AD pathology and clinical progression, indicating a potential role for plasma biomarkers in clinical trials. More research is warranted to develop a robust plasma AD framework.This study aimed to predict brain amyloid beta (Aβ) status in older adults using collected information from an online registry focused on cognitive aging.
Aβ positron emission tomography (PET) was obtained from multiple in-clinic studies. Using logistic regression, we predicted Aβ using self-report variables collected in the Brain Health Registry in 634 participants, as well as a subsample (N=533) identified as either cognitively unimpaired (CU) or mild cognitive impairment (MCI). https://www.selleckchem.com/products/ulk-101.html Cross-validated area under the curve (cAUC) evaluated the predictive performance.
The best prediction model included age, sex, education, subjective memory concern, family history of Alzheimer's disease, Geriatric Depression Scale Short-Form, self-reported Everyday Cognition, and self-reported cognitive impairment. The cross-validated AUCs ranged from 0.62 to 0.66. This online model could help reduce between 15.2% and 23.7% of unnecessary Aβ PET scans in CU and MCI populations.
The findings suggest that a novel, online approach could aid in Aβ prediction.
The findings suggest that a novel, online approach could aid in Aβ prediction.Safety nets are expanding in African countries as a policy instrument to alleviate poverty and food insecurity. Whether safety nets have improved household food security and child diet and nutrition in sub-Saharan Africa has not been well documented. This paper takes the case of Ethiopia's Productive Safety Net Program (PSNP) and provides evidence of the impact of safety nets on household food security and child nutritional outcomes. Prior studies provide inconclusive evidence as to whether PSNP has improved household food security and child nutrition. These studies used analytical approaches that correct for selection bias but have overlooked the effect of time-varying confounders that might have resulted in biased estimation. Given that household food security status is both the criteria for participation and one of the desirable outcomes of the program, estimating the causal impact of PSNP on household food security and child nutrition is prone to endogeneity due to selection bias and time-varying confounders. Therefore, the objectives of this paper are (1) to examine the impacts of PSNP on household food security, child meal frequency, child diet diversity, and child anthropometry using marginal structural modeling approach that takes into account both selection bias and time-varying confounders and (2) to shed some light on policy and programmatic implications. Results show that PSNP has not improved household food insecurity, child dietary diversity, and child anthropometry despite its positive impact on child meal frequency. Household participation in PSNP brought a 0.308 unit gain on child meal frequency. Given the consequence of food insecurity and child undernutrition on physical and mental development, intergenerational cycle of poverty, and human capital formation, the program would benefit if it is tailored to nutrition-specific and nutrition-sensitive interventions.